Dynamic Asymmetric Tail Dependence in Asian Developed Futures Markets

Abstract

This paper employs three two-parameter Archimedean copulas (BB1, BB4, and BB7) to investigate dynamic asymmetric tail dependence in Asian developed futures markets over the post-crisis period. The estimation is consistent and asymptotic with a careful implementation of the two-stage method. Unlike previous empirical research, we first let each marginal model follow a conditional skewed-t distribution. Based on robust inference for dynamic marginal models, it is found that higher moments of each filtered index return series are significantly time-dependent. We then extend those three two-parameter copulas incorporating time-varying tail dependence to capture dynamic asymmetries. The estimation results of the copulas provide strong evidence of asymmetric tail dependence in Asian developed futures markets. Moreover, based on the goodness-of-fit tests, we find that the model BB7 is the optimal one. The model's results suggest that the probability of dependence in bear markets is higher than in bull markets in the post-crisis period. This further confirms downside dependent risk in Asian developed futures markets. Our empirical findings provide a basis for hedging downside dependent risk, and thus make a contribution to the literature of financial risk management.

Keywords: Tail dependence, Time varying two-parameter copula, Two-Stage Estimation, Threshold GARCH, Conditional skewed-t distribution, Goodness-of-fit test